Multi-Frequency Mm-Wave Wireless Channel Measurements and Modelling for 5G Networks in Built-Environments
Notice bibliographique
Résumé
Millimeter-wave (Mm-Wave) wireless communication with a large transmission bandwidth is viewed as a key technology for the fifth generation (5G) wireless systems. The use of the mm-Wave band will considerably extend the channel capacity of indoor wireless communication networks. Therefore, indoor channel measurements and modeling at these frequency bands are essential for a good understanding of the radio propagation channel characteristics for the evaluation of future mm-Wave system performance and the design of 5G radio networks. This thesis addresses the channel sounding measurement, characterization, and modeling of mm-Wave channels in typical 5G Built-Environments (BEs) scenarios. Furthermore, a comprehensive summary of the radio wave propagation mechanisms, mm-Wave channel propagation characteristics, mm-Wave channel modeling approaches, channel measurement methods, channel measurement setups, and Durham University’s channel sounder is given. Extensive multi-frequency indoor mm-Wave channel measurements in multi-scenario are performed in the WaveComBE project at the science site campus of Durham University, UK. The key works and novelties of this thesis are summarized as follows: First, Omni-directional Multi-band Measurements and Modeling: indoor omni-directional multi-band measurements covering nine frequency bands within the 0.6-73 GHz range are described. The measurements were conducted with the research team at Durham University in various indoor environments, including meeting rooms and office room, using two state of art Durham University's channel sounders. Single-frequency path loss models and multi-frequency path loss models are thoroughly studied to investigate path loss coefficients for each measured band as well as a single set of coefficients across a wide range of measured bands for a frequency-dependent path loss model. The root mean square (RMS) delay spread (DS) values were estimated and presented across the measured frequency range. The frequency dependency of the delay spread based on a 3rd Generation Partnership Project (3GPP-like) model is also presented and discussed. These measurements data included two inputs to update the International Telecommunications Union-Radiocommunication (ITU-R P.1238-10). Second, Effect of Bandwidth on Mm-Wave Channel Characterization: wideband indoor channel measurements are conducted in three of the frequency bands (39 GHz, 60 GHz, and 70 GHz) identified by the World Radiocommunications Conference in 2019 (WRC-19) for 5G networks. The measurements were carried out in a seldom reported environment, such as a corridor-style set up with computer clusters and factory-like environments. The wideband channel parameters were measured and estimated with a bandwidth of 0.5, 1, 1.5, and 2 GHz for the first time. The impacts of the processing bandwidth on the mm-Wave channel characteristics are studied, including power delay profile (PDP), RMS delay spread, Rician K-factor, coherence bandwidth (B_c), and path loss (PL). Third, 3D Multi-band Mm-Wave Indoor Directional Channel Measurements: three-dimensional (3D) wideband multi-frequency directional measurements covering both azimuth and elevation domains, in factory, corridor, and computer laboratory environments are performed at four bands in the frequency range of 13 GHz to 73 GHz. The measurements were conducted using the same multi-band chirp-based channel sounder by employing the rotated directional antenna-based (RDA) method. Different propagation channel parameters were estimated and compared for different possible antenna alignments (angular orientations) between the transmitter (Tx) and the receiver (Rx) across the measured bands. Moreover, the effects of the antenna pattern (antenna directivity) on the mm-Wave channel propagation properties, such as the average power delay profile, RMS delay spread, and angular spread (AS), were investigated. Fourth, SISO, SIMO, and MIMO Indoor Directional Channel Measurements: wideband single-input single-output (SISO) and single-input multiple-output (SIMO) indoor directional measurements were conducted at the 60 GHz Wireless Gigabit Alliance (WiGig) in a meeting room, a classroom, a seminar room, an office room, and a computer laboratory. Furthermore, multiple-input multiple-output (MIMO) dual polarised measurements with 2 x 2 antenna configurations were carried out in an office room and a computer laboratory in the V-band (50-75 GHz). The measurements were performed using the multi-band chirp-based channel sounder by employing the RDA method. The channel parameters were measured and estimated for different possible antenna orientations. The impacts of polarization on the channel parameters, the frequency dependency of the delay spread based on the 3GPP model, and the delay spread model as well as the angular spread model as a function of the size of the environment based on the ITU model are thoroughly studied. Fifth, Mm-Wave Indoor Human Blockage Measurements and Modeling: real-time measurements and theoretical modelling are used to investigate the shadowing loss of the human body at multiple mm-Wave bands. Different kinds of human blockage (HB) measurements were conducted. The measurements were performed at four frequency bands in the range of 24 GHz to 73 GHz, in a corridor-style set up with computer clusters, where no recent HB measurements have been reported in such a scenario. Blockage models such as the Kirchhoff knife-edge diffraction (KED) model, METIS (mobile and wireless communications enablers for the twenty-twenty information society) KED model, and geometrical theory of diffraction (GTD) model were applied to simulate the human body shadowing (HBS) effects. In conclusion, this thesis has produced a large number of works on mm-Wave channel sounding measurements, channel parameter estimations, and channel modeling approaches. The results of this thesis will be valuable for the future mm-Wave communication systems design in indoor environments.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».